Intelligent communication channel determination

ABSTRACT

In response to detecting that a user of a service provider requires assistance, a computer system determines a predicted user intent associated with the user based on monitoring activity associated with the user, and further determines that a first communication channel corresponds to the determined predicted user intent and causes a communication to be initiated with the user utilizing the first communication channel. The computer system determines a user-initiated intent based on analyzing input received from the user, and based on the user-initiated intent, determines if the user-initiated intent corresponds to the predicted user intent. In response to determining that the user-initiated intent does not correspond to the predicted user intent, the computer system determines that a second communication channel corresponds to the user-initiated intent and causes the communication with the user to be switched to the second communication channel.

TECHNICAL FIELD

The present disclosure relates to customer service, and moreparticularly to a system and method for utilizing intelligence toeffectively determine the appropriate communication channel tocommunicate with customers and users.

BACKGROUND

Providing quality customer service is tantamount to running a successfulcompany. However, providing quality and effective customer service isnot only limited to the interactions between a customer service agentand a customer, but also includes the manner in which service isprovided as well as the time it takes to provide the service. In manycases, corporations consider providing human to human customer serviceto be the primary way of achieving quality service, however, providinghuman to human customer service may be costly to provide. Therefore,there is a need for a system that can dynamically determine theappropriate channel of customer service to provide a customer in orderto ensure that cost-effective and quality service is provided.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an intelligent service system, in accordance with anembodiment.

FIG. 2 is a flowchart illustrating the operations of the decisionapplication of FIG. 1 in determining one or more appropriatecommunication channels for a user, and further initiating acommunication with the user via the best determined communicationchannel, in accordance with an embodiment.

FIG. 3 is a flowchart illustrating the operations of the decisionapplication of FIG. 1 in determining an appropriate communicationchannels for a first predicted user intent and then determining switchto another communication channel based on determining a second predicteduser intent, in accordance with an embodiment.

FIG. 4 is a block diagram depicting the hardware components of theintelligent service system of FIG. 1, in accordance with an embodiment.

DETAILED DESCRIPTION

Embodiments of the present disclosure provide a system, method, andprogram product. In the example embodiment, in response to detectingthat a user of a service provider requires assistance, a computer systemdetermines a predicted user intent associated with the user based onmonitoring activity associated with the user. The computer systemdetermines that a first communication channel corresponds to thedetermined predicted user intent. The computer system causes acommunication to be initiated with the user utilizing the firstcommunication channel. The computer system determines a user-initiatedintent based on analyzing input received from the user. In response todetermining the user-initiated intent, the computer system determines ifthe user-initiated intent corresponds to the predicted user intent. Inresponse to determining that the user-initiated intent does notcorrespond to the predicted user intent, the computer system determinesthat a second communication channel corresponds to the user-initiatedintent. In response to determining that the second communication channelcorresponds to the user-initiated intent, the computer system causes thecommunication with the user to be switched to the second communicationchannel.

In the example embodiment, the present disclosure describes a solutionthat describes a solution that identifies that a user requiresassistance, such as with an application, product, or service.Furthermore, the solution identifies and transmits user informationwhich may include one or more actions taken by the user and useridentification information (among other things). In addition, thesolution may determine a predicted intent, and based on the predictedintent may determine an appropriate channel(s) to initiate engagementwith the user. Furthermore, the solution may determine a user-initiatedintent based on received user input. The present solution may thendetermine if there is a convergence between the user-initiated intentand the predicted intent, and if there is not a convergence, the presentsolution may determine an appropriate communication channel based on theuser-initiated intent and switch the communication channel to the newlydetermined communication channel. Furthermore, determining theappropriate communication channel may be based on the intent, anengagement score associated with the customer, and channel availability.

Embodiments of the present disclosure will now be described in detailwith reference to the accompanying Figures.

FIG. 1 illustrates intelligent service system 100, in accordance with anembodiment. In the example embodiment, intelligent service system 100includes device 110, server 120, and server 140 interconnected vianetwork 130.

In the example embodiment, network 130 is the Internet, representing aworldwide collection of networks and gateways to support communicationsbetween devices connected to the Internet. Network 130 may include, forexample, wired, wireless or fiber optic connections. In otherembodiments, network 130 may be implemented as an intranet, a Bluetoothnetwork, a local area network (LAN), or a wide area network (WAN). Ingeneral, network 130 can be any combination of connections and protocolsthat will support communications between computing devices, such asbetween device 110 and server 140.

In the example embodiment, server 120 includes database 122 and database124. In the example embodiment, server 120 may be a desktop computer, alaptop computer, a tablet computer, a mobile device, a handheld device,a thin client, or any other electronic device or computing systemcapable of receiving and sending data to and from other computingdevices, such as device 110, via network 130. Although not shown,optionally, server 120 can comprise a cluster of servers executing thesame software to collectively process requests as distributed by afront-end server and a load balancer. In the example embodiment, server120 is a computing device that is optimized for the support of databasesthat reside on server 120, such as database 122, and for the support ofrequests related to database 122. Server 120 is described in more detailwith regard to the figures.

In the example embodiment, database 122 is a database that includes userinformation corresponding to one or more users of a service providerassociated with server 140. In the example embodiment, the userinformation may include transactional information, preferenceinformation, user biographic information, user interests, userinteractions with other users of the service provider, a user's priorquestions regarding the utilization of a service providerapplication(s), and additional user interactions with a service providerapplication(s). For example, if the service provider is a paymentservice provider, database 122 may include transactional information,user payment information, user authentication information, invoicescorresponding to each user, payment preference information, refunds,along with the information stated above. In the example embodiment,database 122 may include additional information, such as additionalinformation corresponding to a history of one or more users with aservice provider, and the lists provided above are not intended to beexhaustive. Database 122 is described in more detail with regard to thefigures.

In the example embodiment, database 124 is a database that includes oneor more user intents and one or more corresponding user channels. Forexample, database 124 may include a user intent of resetting a passwordwith one or more appropriate communication channels (such as a directphone call) listed in association with the user intent. Furthermore,database 124 may include a history of mappings applied to a specificuser. For instance, referring to the example above, if the user wasprovided help with resetting a password via a first communicationchannel, and it was confirmed that the issue was resolved, the firstcommunication channel may be mapped to the user intent of resetting apassword. In other embodiments, where there are multiple channelsassociated with the intent of resetting a password, a weight valueassociated with the first communication channel may be adjusted upwardeach time that the channel is utilized to solve the issue successfully.This process may be utilized to build a mapping system within database124 between user intent and one or more appropriate communicationchannels. In one or more embodiments, database 124 may include a custommapping (based on previous actions/intents of a specific user) and mayalso include a general mapping (based on actions of a plurality ofusers). With regard to the general mapping, if the number of instancesthat a communication channel is verified as corresponding to a userintent (communication channel is utilized to successfully resolve theissue) exceeds a threshold number, a record associating the user intentto the communication channel may be maintained in the general mappingportion of database 124. Furthermore, if the number of instances that acommunication channel is verified as not resolving an issue associatedwith a user intent exceeds a threshold number, a record associating theuser intent to the communication channel may be updated to bedisassociated with the user intent (within the general mapping or custommapping portion of database 124. Database 124 is described in moredetail with regard to the figures.

In the example embodiment, device 110 includes client application 112.In the example embodiment, device 110 may be a desktop computer, alaptop computer, a tablet computer, a mobile device, a handheld device,a thin client, or any other electronic device or computing systemcapable of receiving and sending data to and from other computingdevices, such as server 120, via network 130. Device 110 is described inmore detail with regard to the figures.

In the example embodiment, client application 112 is a client-sideapplication, corresponding to the server-side application 142, that iscapable of transmitting requests to application 142 and is furthercapable of providing received information to a user of device 110 via auser interface. In the example embodiment, client application 114 may bean e-commerce application, a financial application, a social mediaapplication, a merchant application, a service provider application, oranother type of application. Client application 112 is described in moredetail with regard to the figures.

In the example embodiment, server 140 includes application 142, decisionapplication 144, and intent prediction model 146. In the exampleembodiment, server 140 may be a desktop computer, a laptop computer, atablet computer, a mobile device, a handheld device, a thin client, orany other electronic device or computing system capable of receiving andsending data to and from other computing devices, such as device 110,via network 130. Furthermore, in the example embodiment, server 140 is acomputing device that is optimized for the support of applications thatreside on server 140, such as application 142. Although not shown,optionally, server 140 can comprise a cluster of servers executing thesame software to collectively process requests as distributed by afront-end server and a load balancer. Server 140 is described in moredetail with regard to the figures.

In the example embodiment, application 142 is a server-side application,corresponding to the client-side payment applications such as clientapplication 112. Application 142 is capable of receiving informationfrom client payment applications and further capable of responding torequests from corresponding client payment applications. In addition, inthe example embodiment, application 142 is capable of utilizing clientapplication 112 to monitor activity within client application 112 andalso on device 110. Furthermore, application 142 may be an e-commerceapplication, a financial application, a social media application, amerchant application, a service provider application, or another type ofapplication. Application 142 is described in more detail with regard tothe figures.

In the example embodiment, intent prediction model 146 is a model thatis capable of receiving input and providing a prediction outputcorresponding to a user intent. For example, intent prediction model 146may receive input corresponding to a user's action within clientapplication 112 (FAQ visited), along with additional information todetermine a predicted user intent (such as password reset). Intentprediction model 146 is described in more detail with regard to thefigures.

In the example embodiment, decision application 144 is an applicationthat is capable of determining a user-initiated intent based on userinformation received from device 110. In the example embodiment,decision application 144 may be partially or fully integrated withapplication 142, and further, may utilize application 142, as describedabove, to monitor activity on device 110 and obtain user information.Furthermore, decision application 144 is capable of determining apredicted intent based on the monitored activity and determining one ormore appropriate communication channels for the user based on thepredicted intent. In addition, decision application 144 is capable ofdetermining a user-initiated intent based on provided user input, andmay compare the user-initiated intent to the predicted intent(determined via intent prediction model 146) in order to determine ifthey correspond to each other. In addition, based on determining thatthey do not correspond to each other, decision application 144 iscapable of determining one or more appropriate communication channelsthat corresponds to the user-initiated intent. Further, in the exampleembodiment, decision application 144 is capable of changing thecommunication channel to a best communication channel of the one or moreappropriate communication channels that correspond to the user-initiatedintent. Decision application 144 is described in further detail withregard to the figures.

FIG. 2 is a flowchart illustrating the operations of decisionapplication 144 in determining one or more appropriate communicationchannels for a user, and further initiating a communication with theuser via the best determined communication channel, in accordance withan embodiment.

In the example embodiment, decision application 144 may utilizeapplication 142 (via client application 112) to detect that a user, suchas the user of device 110, is indicating that assistance is required(step 202). In the example embodiment, decision application 144 may befully or partially integrated with application 142 and may utilizeclient application 112 to monitor actions within client application 112(or on device 110). In other embodiments, decision application 144 maybe a separate application from application 142 and may instead receivean indication that a user requires assistance from application 142. Forexample, a user of device 110 may access a FAQ question within clientapplication 112 that corresponds to a monetary restriction that may beassociated with certain users, which prevent the certain users fromtransferring large amounts of money using the application. In addition,client application 112 may monitor an amount of time that the user ofdevice 110 spends on a specific FAQ question or multiple FAQ questions,and based on that, determine that the user requires assistance. Inaddition, client application 112 may also determine that the user ofdevice 110 requires assistance based on monitoring other actions, suchas if the user has entered incorrect login credentials a thresholdamount of times, or if the user has spent greater than a thresholdamount of time viewing a specific displayed content, or if the userattempts a transaction that fails. In other embodiments, decisionapplication 144 may monitor or communicate with other devices that aremonitoring one or more activities of the user of device 110. Forexample, decision application may communicate with an interactive voiceresponse (IVR) server to identify that the user of device 110 hasprovided input that indicates assistance is required.

Based on detecting an indication that the user of device 110 requiresassistance, decision application 144 may identify user informationcorresponding to the user of device 110. In the example embodiment,decision application 144 may utilize a device identifier or logincredentials associated with the user of device 110 to identify a recordin database 122 that corresponds to the user. Decision application 144may then retrieve user information associated with the user of device110 from database 122. In the example embodiment, as stated above, theuser information may include user transactional information, userpreference information, user biographic information, user interests,user interactions with other users of the service provider, a user'sprior questions regarding the utilization of a service providerapplication(s), and additional user interactions with a service providerapplication(s), such as application 142 (and its clients).

In the example embodiment, decision application 144 may determine apredicted user intent of the user of device 110 by inputting themonitored user activity into intent prediction model 146 (step 206).Furthermore, in one or more embodiments, decision application 144 mayadditionally input one or more portion of the identified userinformation into intent prediction model 146 as well. Intent predictionmodel 146 may utilize a gradiant boosting techniques to determine apredicted user intent

In the example embodiment, intent prediction model 146 may analyze themonitored user activity and may identify one or more than one potentialuser intents (with each being associated with a likelihood value). Forexample, if the user of device 110 views three different FAQs thatpertain to three different matters, intent prediction model 146 may takeinto account how much time was spent viewing each FAQ, other useractivity related to each FAQ (such as a web search done in a web browserthat corresponds to the FAQ, or an unsuccessful login attempt thatrelates to a login FAQ), and may further take previous user activityinto account. For example, if the user of device 110 has previously hadmultiple issues that relate to a first FAQ of the three viewed FAQ,intent prediction model 146 may determine that the previous activityincreases the likelihood that the predicted user intent corresponds tothe issue that relates to the first FAQ. Furthermore, other types ofmonitored activity, such as input into an IVR may also be taken intoaccount.

Furthermore, in one or more embodiments, prior to being utilized, intentprediction model 146 may be trained using a plurality of datacorresponding to user activity. For example, decision application 144may input user activity and user information into intent predictionmodel 146 and adjust weight values and other characteristics of themodel until the output (predicted user intent) matches a desired result.

In the example embodiment, decision application 144 may determine anappropriate communication channel based on the predicted user intent(step 208). In the example embodiment, decision application 144 mayaccess database 124 to determine one or more communication channels thatcorrespond to the predicted user intent. In one or more embodiments,examples of communication channels may be email, text message, IVR, alive phone call with a customer service agent, a chat session, or anyother known communication method. For example, if the predicted userintent is resetting a password, decision application 144 may refer todatabase 124 and determine that a first communication channel (such as achat), a second communication channel (such as an email correspondenceoption), and a third communication channel (such as a phone call option)are listed within database 124 in association with the predicted userintent of resetting a password. Furthermore, each of the communicationchannels may be associated with one or more specific weight values withregard to the predicted user intent. In the example embodiment, theweight values may correspond to the likelihood of success that theparticular communication channel has for the particular issue (predicteduser intent), the cost of utilizing the particular channel for theparticular issue, the availability of the communication channel (basedon hours of operation, current wait time information, etc.), and mayalso be based on user preferences. Referring to the example above, atotal weight value (or multiple individual weight values) may bedetermined by decision application 144 in association with the first,second and third communication channels. Decision application 144, inthe case of a total weight value for each of the channels, may determinewhich of the channels has the highest weight value.

In other embodiments, the cost of utilizing the particular channel maybe utilized as a second level determination mechanism in determining anappropriate channel to initiate an engagement with the user of device110. For example, decision application 144 may determine a total weightvalue that corresponds to the likelihood of success that the particularcommunication channel has for the particular issue (predicted userintent) and the availability of the communication channel for each ofthe first, second, and third channel referenced above. Decisionapplication 144 may then utilize the cost of each of the communicationchannels to serve as factor in determining an appropriate channelamongst the (highest rated) channels that are within a thresholdpercentage (or threshold weight value) of each other. Referring to theexample above, if the first and second channel are the two highest ratedcommunication channels based on the associated total weight values, andthe difference between the total weight value of the first channel andthe second channel is less than a threshold percentage, decisionapplication 144 may determine the associated cost of each communicationchannel and, identify the channel with the lowest associated cost as themost appropriate (or highest rated) communication channel for theparticular issue (predicted user intent).

In further embodiments, an engagement score corresponding to the user ofdevice 110 may also be taken into account. For example, decisionapplication 144 may analyze user information retrieved from database122, to determine an engagement score associated with the user of device110. The engagement score may be based on a variety of factors includingan amount that the user of device 110 utilizes the service providerassociated with application 142, a transactional amount associated withthe user of device 110 with regard to the service provider, a usersatisfaction score with the service provided by the service provider,and a variety of other factors that corresponds to engagement betweenthe user of device 110 and the service provider associated withapplication 142. In the further embodiments, decision application 144may re-rate the hierarchy of the one or more communication channelsassociated with the predicted user intent of the user of device 110,based on the engagement score of the user of device 110. Referring tothe example provided above, if the first and second communicationchannel are determined to be the highest rated channels for theparticular predicted user intent based on the total weight valueassociated with each communication channel (with the associated cost notbeing included as a factor for the total weight values), decisionapplication 144 may determine if the total weight values of the firstand second channel are within a threshold percentage of each other, andif so may determine to rate the first communication channel higher thanthe second communication channel based on determining that a costassociated with the first channel is lower than a cost associated withthe second channel. However, in these further embodiments, decisionapplication 144 may take the engagement score of the user of device 110into account, and based on the engagement score of the user of device110 being above a threshold score, decision application 144 may rate orre-rate the hierarchy of communication channels so that thecommunication channel with the highest total weight value is rated asthe best or most appropriate communication channel for the particularissue (or predicted user intent) regardless of the cost difference.

Furthermore, in one or more additional embodiments, decision application144 may determine an availability score associated with the determinedone or more communication channels that correspond to the predicted userintent. The availability score may be utilized in rating or re-ratingthe hierarchy of communication channels and/or determining anappropriate communication channel for the particular issue. For example,if a particular channel, such as a call with a call center, isunavailable due to the call center staff being unavailable at the timethat the issue is identified, the channel may be re-rated to have alower score (and in one or more instance be rated to have the lowesttotal weight value amongst the determined one or more communicationchannels). Furthermore, a wait time associated with each of the one ormore communication channels may be utilized in determining the totalweight score of each of the one or more communication channels (orre-rating the one or more communication channels).

Based on the determination of the most appropriate communicationchannel, decision application 144 may then initiate communication withthe user of device 110 utilizing the determined appropriatecommunication channel (step 210). For example, if decision application144 determines that a first communication channel (a chat) is the mostappropriate communication channel for a predicted user intent (using thetechniques described above), decision application 144 may then initiatea chat with the user of device 110. Furthermore, within thecommunication channel, decision application 144 may provide informationcorresponding to the predicted intent (which, in some instances, may beprovided prior to receiving a user response). For example, decisionapplication 144 may initiate a chat window with the user of device 110and immediately provide information related to the resetting a password(the predicted intent) prior to the user providing a response orcommunication within the chat window.

In the example embodiment, decision application 144 may determine auser-initiated intent (step 212). In the example embodiment, decisionapplication 144 may determine a user-initiated intent based on userinput received from the user of device 110. In the example embodiment,decision application 144 may receive the user input indicating theuser-initiated intent within the determined communication channelutilized to initiate communication with the user of device 110. Forexample, if the determined communication channel is a chat session,decision application 144 may detect a user input via a chatcommunication that may indicate a particular issue that the user ishaving (user-initiated intent). In other embodiments, the user inputindicating the user-initiated intent may be received in a differentcommunication channel than the determined communication channel.

In the example embodiment, decision application 144 determines if theuser-initiated intent corresponds to the predicted user intent (decision214). In the example embodiment, decision application 144 determines ifthe user-initiated intent matches or substantially matches the predicteduser intent. For example, if the user-initiated intent is associatedwith issues with a password reset and predicted user intent isassociated with issues with login, decision application 144 maydetermine that that the user-initiated intent substantially matches thepredicted intent. In the example embodiment, if decision application 144determines that the user-initiated intent corresponds to the predictedintent (decision 214, “YES” branch), decision application 144 maydetermine to continue communicating with the user regarding theparticular issue associated with the user-initiated intent in thecommunication channel used to initiate communication with the user ofdevice 110.

In the example embodiment, if decision application 144 determines thatthe user-initiated intent does not correspond to the predicted intent(decision 214, “NO” branch), decision application 144 may determine anappropriate communication channel based on the user-initiated intent(step 216). In the example embodiment, decision application 144 mayrefer to database 124 in order to determine one or more communicationchannels that correspond to the user-initiated intent. Furthermore,decision application 144 may determine an appropriate communicationchannel from the one or more communication channels in a similar manneras described above (in the discussion of step 208).

Furthermore, if the determined appropriate communication channel thatcorresponds to the user-initiated intent is different than thecommunication channel utilized to initiate communication with the userof device 110, decision application 144 may change the communicationchannel and re-engage with the user of device 110 using thecommunication channel that corresponds to the user-initiated intent(step 218). In addition, in one or more embodiments, if the determinedappropriate communication channel that corresponds to the user-initiatedintent is the same as the communication channel utilized to initiatecommunication with the user of device 110, decision application 144 maycontinue to engage with the user of device 110 using the communicationchannel utilized to initiate communication with the user of device 110,but may provide updated information that corresponds to theuser-initiated intent to an agent (automated or human) associated withthe communication channel.

Furthermore, in additional embodiments, decision application 144 maydetermine one or more appropriate channels for the predicted user intentutilizing one or more of the techniques described above, and thenprovide a hierarchy of the one or more appropriate channels to the userof device 110 to select. The user of device 110, may then provide inputon what he/she feels is the most appropriate communication channel ormay utilize a preferred communication channel to contact the serviceprovider associated with application 142.

In one or more embodiments, decision application 144 may monitoractivity on device 110 and determine a predicted intent, but the user ofdevice 110 may decide to identify a communication channel and initiatecommunication with the service provider associated with application 142.If decision application 144 determines an appropriate communicationchannel that corresponds to the predicted user intent (in the mannerdescribed above) and if the communication channel utilized by the userof device 110 does not match the determined appropriate communicationchannel, decision application 144 may automatically change thecommunication channel to the determined appropriate communicationchannel that corresponds to the predict user transmit or may transmit anotification to the user of device 110 that includes a selectableelement, that when selected may cause the user of device 110 to connectto the service provider via the determined appropriate communicationchannel (and may also end the current communication session initiated bythe user of device 110). In one or more embodiments, the notificationmay also include information corresponding to the predicted user intentso the user of device 110 can verify if the predicted user intent isaccurate prior to switching communication channels.

FIG. 3 is a flowchart illustrating the operations of the decisionapplication 144 in determining an appropriate communication channels fora first predicted user intent and then determining to switch to anothercommunication channel based on determining a second predicted userintent, in accordance with an embodiment.

In additional embodiments, upon initiation of communication with theuser of user device via an appropriate communication channel determinedbased on the predicted user intent, decision application 144 maycontinue to monitor user activity on device 110 and utilize thetechniques discussed to update the predicted user intent based on thecontinued monitored activity.

Referring to FIG. 3, in the example embodiment, decision application 144may detect that the user of device 110 requires assistance based onmonitory user activity, as described above (step 302). Decisionapplication 144 may then identify user information (step 304), andfurther determine a first predicted user intent (step 306) and determinean appropriate communication channel based on the first predicted userintent, as described above (step 308). In the example embodiment,decision application 144 may then determine a second predicted userintent based on continued monitored activity (step 310), and furtherdetermine if the second predicted user intent corresponds to the firstpredicted user intent (decision 312). If decision application 144determines that the second predicted user intent corresponds to thefirst predicted user intent (decision 312, “YES” branch), decisionapplication 144 may continue to engage with the user of device 110 viathe determined communication channel corresponding to the firstpredicted user intent. If decision application 144 determines that thesecond predicted user intent does not correspond to the first predicteduser intent (decision 312, “NO” branch), decision application 144 maydetermine a communication channel that corresponds to the secondpredicted user intent (in the same manner as the initial communicationchannel is determined) (step 314), and further may change thecommunication channel, based on determining that the communicationchannel that corresponds to the second predicted user intent isdifferent than the communication channel that corresponds to the firstpredicted user intent (step 316).

For example, if based on the continued monitored activity, decisionapplication 144 determines that the predicted user intent has changedfrom the initial predicted user intent, decision application 144 maythen determine if the newly determined predicted user intent correspondsto a different communication channel than the communication channelcurrently being utilized to communicate with the user. Based ondetermining that the newly determined predicted user intent correspondsto a different communication channel (a second channel), decisionapplication 144 may stop communication via the original channel andre-engage with the user via the second channel. In one or moreembodiments, decision application 144 may continue with the steps ofdetermining a user-initiated intent and determining if the communicationchannel needs to be changed based on the user-initiated intent asdescribed above (steps 212 to 218).

Furthermore, in one or more embodiments, while FIG. 1 the serviceprovider is depicted as maintaining and supporting application 142 (andall corresponding client applications), in other embodiments, theservice provider may maintain a website that the user of device 110 mayaccess. Therefore, the monitored activity discussed with regard to step202 may correspond to the activity of the user of device 110 on one ormore webpages of the website of the service provider. Furthermore, theuser information of the user of device 110 may correspond to the use ofthe website, and communication channels initiated or provided to theuser of device 110 may be facilitated via the website, such as chatsession that occurs via the website of the service provider.

The foregoing description of various embodiments of the presentdisclosure has been presented for purposes of illustration anddescription. It is not intended to be exhaustive nor to limit thedisclosure to the precise form disclosed. Many modifications andvariations are possible. Such modifications and variations that may beapparent to a person skilled in the art of the disclosure are intendedto be included within the scope of the disclosure as defined by theaccompanying claims.

FIG. 4 depicts a block diagram of components of computing devicescontained in intelligent service system 100 of FIG. 1, in accordancewith an embodiment. It should be appreciated that FIG. 4 provides onlyan illustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be made.

Computing devices may include one or more processors 402, one or morecomputer-readable RAMs 404, one or more computer-readable ROMs 406, oneor more computer readable storage media 408, device drivers 412,read/write drive or interface 414, network adapter or interface 416, allinterconnected over a communications fabric 418. Communications fabric418 may be implemented with any architecture designed for passing dataand/or control information between processors (such as microprocessors,communications and network processors, etc.), system memory, peripheraldevices, and any other hardware components within a system.

One or more operating systems 410, and one or more application programs411, for example, decision application 144, are stored on one or more ofthe computer readable storage media 408 for execution by one or more ofthe processors 402 and by utilizing one or more of the respective RAMs404 (which typically include cache memory). In the illustratedembodiment, each of the computer readable storage media 408 may be amagnetic disk storage device of an internal hard drive, CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk, asemiconductor storage device such as RAM, ROM, EPROM, flash memory orany other computer-readable tangible storage device that can store acomputer program and digital information.

Computing devices may also include a R/W drive or interface 414 to readfrom and write to one or more portable computer readable storage media426. Application programs 411 on the computing devices may be stored onone or more of the portable computer readable storage media 426, readvia the respective R/W drive or interface 414 and loaded into therespective computer readable storage media 408.

Computing devices may also include a network adapter or interface 416,such as a TCP/IP adapter card or wireless communication adapter (such asa 4G wireless communication adapter using OFDMA technology). Applicationprograms 411 on the computing devices may be downloaded to the computingdevices from an external computer or external storage device via anetwork (for example, the Internet, a local area network or other widearea network or wireless network) and network adapter or interface 416.From the network adapter or interface 416, the programs may be loadedonto computer readable storage media 408. The network may comprisecopper wires, optical fibers, wireless transmission, routers, firewalls,switches, gateway computers and/or edge servers.

Computing devices may also include a display screen 420, and externaldevices 422, which may include, for example a keyboard, a computer mouseand/or touchpad. Device drivers 412 interface to display screen 820 forimaging, to external devices 422, and/or to display screen 420 forpressure sensing of alphanumeric character entry and user selections.The device drivers 412, R/W drive or interface 414 and network adapteror interface 416 may comprise hardware and software (stored on computerreadable storage media 408 and/or ROM 406).

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment. However, itshould be appreciated that any particular program nomenclature herein isused merely for convenience, and thus the disclosure should not belimited to use solely in any specific application identified and/orimplied by such nomenclature.

Based on the foregoing, a computer system, method, and computer programproduct have been disclosed. However, numerous modifications andsubstitutions can be made without deviating from the scope of thepresent disclosure. Therefore, the various embodiments have beendisclosed by way of example and not limitation.

Various embodiments of the present disclosure may be a system, a method,and/or a computer program product. The computer program product mayinclude a computer readable storage medium (or media) having computerreadable program instructions thereon for causing a processor to carryout aspects of the present disclosure.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present disclosure may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of thedisclosure. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

What is claimed is:
 1. A computer system, comprising: one or morecomputer-readable memories storing program instructions; and one or moreprocessors configured to execute the program instructions to cause thecomputer system to perform operations comprising: monitoring activityassociated with a user of a service provider, the activity comprising: auser access of a document on a user device, an amount of time spent bythe user viewing a specified content displayed on the user device, anumber of failed user login attempts, or a failed user transaction;detecting, based on the monitoring, that the user requires assistance;in response to the detecting that the user requires assistance,determining a predicted user intent associated with the user based onthe monitoring; determining that a first communication channelcorresponds to the determined predicted user intent; causing acommunication to be initiated with the user utilizing the firstcommunication channel; detecting a user input through the firstcommunication channel; analyzing the detected user input; determining,based on the analyzing, a user-initiated intent, wherein the determiningthe user-initiated intent is performed separately from the determiningthe predicted user intent; in response to determining the user-initiatedintent, determining if the user-initiated intent corresponds to thepredicted user intent; in response to determining that theuser-initiated intent does not correspond to the predicted user intent,determining that a second communication channel corresponds to theuser-initiated intent, the second communication channel being differentfrom the first communication channel; in response to determining thatthe second communication channel corresponds to the user-initiatedintent, transmitting a notification to the user device via the firstcommunication channel, the notification including a selectable element,the notification further including information corresponding to thepredicted user intent; detecting a user selection of the selectableelement; and causing, in response to the detecting of the user selectionof the selectable element, the communication with the user to beswitched to the second communication channel and terminating thecommunication utilizing the first communication channel.
 2. The computersystem of claim 1, wherein the document comprises a frequently askedquestions (FAQ) document.
 3. The computer system of claim 1, wherein thedetermining that the first communication channel corresponds to thedetermined predicted user intent includes: accessing a database;determining, from the database, that a first plurality of communicationchannels are associated with the determined predicted user intent; andselecting the first communication channel from the first plurality ofcommunication channels as corresponding to the determined predicted userintent based at least on a total weight score associated with the firstcommunication channel.
 4. The computer system of claim 3, wherein thefirst plurality of communication channels includes the firstcommunication channel and the second communication channel, and whereinthe total weight score associated with the first communication channelis higher than a total weight score associated with the secondcommunication channel.
 5. The computer system of claim 3, wherein thefirst plurality of communication channels includes the firstcommunication channel and the second communication channel, and whereinthe total weight score associated with the first communication channelis lower than a total weight score associated with the secondcommunication channel, and wherein a cost associated with the secondcommunication channel is higher than a cost associated with the firstcommunication channel.
 6. The computer system of claim 3, wherein theselecting the first communication channel from the first plurality ofcommunication channel as corresponding to the determined predicted userintent is further based on an engagement score associated with the user.7. The computer system of claim 1, wherein the determining that thesecond communication channel corresponds to the user-initiated intentcomprises: presenting, to the user, a second plurality of communicationchannels as potential communication channels to replace the firstcommunication channel; receiving, from the user, a selection of one ofthe communication channels from the second plurality of communicationchannels; and determining that the one of the communication channelsselected by the user is the second communication channel.
 8. Anon-transitory computer-readable medium storing computer-executableinstructions, that in response to execution by one or more hardwareprocessors, causes the one or more hardware processors to performoperations comprising: monitoring activity associated with a user of aservice provider, the activity comprising: a user access of a documenton a user device, an amount of time spent by the user viewing aspecified content displayed on the user device, a number of failed userlogin attempts, or a failed user transaction; predicting, based on themonitoring, that the user requires assistance; determining a predicteduser intent associated with the user based on the monitoring;determining that a first communication channel corresponds to thedetermined predicted user intent; causing a communication to beinitiated with the user utilizing the first communication channel;detecting a user input through the first communication channel;analyzing the detected user input; determining, based on the analyzing,a user-initiated intent, wherein the determining the user-initiatedintent is performed separately from the determining the predicted userintent; in response to determining the user-initiated intent,determining if the user-initiated intent corresponds to the predicteduser intent; in response to determining that the user-initiated intentdoes not correspond to the predicted user intent, determining that asecond communication channel corresponds to the user-initiated intent,the second communication channel being different from the firstcommunication channel and being determined at least in part based onfeedback received from the user; in response to determining that thesecond communication channel corresponds to the user-initiated intent,transmitting a notification to the user device via the firstcommunication channel, the notification including a selectable element,the notification further including information corresponding to thepredicted user intent; detecting a user selection of the selectableelement; and causing, in response to the detecting of the user selectionof the selectable element, the communication with the user to beswitched to the second communication channel and terminating thecommunication utilizing the first communication channel.
 9. Thenon-transitory computer-readable medium of claim 8, wherein the documentcomprises a frequently asked questions (FAQ) document.
 10. Thenon-transitory computer-readable medium of claim 8, wherein thedetermining that the first communication channel corresponds to thedetermined predicted user intent includes: accessing a database;determining, from the database, that a first plurality of communicationchannels are associated with the determined predicted user intent; andselecting the first communication channel from the first plurality ofcommunication channels as corresponding to the determined predicted userintent based at least on a total weight score associated with the firstcommunication channel, and a cost associated with the firstcommunication channel.
 11. The non-transitory computer-readable mediumof claim 10, wherein the first plurality of communication channelsincludes the first communication channel and the second communicationchannel, and wherein the total weight score associated with the firstcommunication channel is higher than a total weight score associatedwith the second communication channel.
 12. The non-transitorycomputer-readable medium of claim 10, wherein the first plurality ofcommunication channels includes the first communication channel and thesecond communication channel, and wherein the total weight scoreassociated with the first communication channel is lower than a totalweight score associated with the second communication channel, whereinthe total weight score associated with the first communication channelis within a threshold percentage of the total weight score associatedwith the second communication channel, and wherein the cost associatedwith the second communication channel is higher than a cost associatedwith the first communication channel.
 13. The non-transitorycomputer-readable medium of claim 10, wherein the selecting the firstcommunication channel from the first plurality of communication channelas corresponding to the determined predicted user intent is furtherbased on an engagement score associated with the user.
 14. Thenon-transitory computer-readable medium of claim 8, wherein the firstcommunication channel or the second communication channel comprises anemail, a text message, a phone call, an IVR call, or a chat session. 15.A method, comprising: monitoring, by a computer system, activityassociated with a user of a service provider, the activity comprising: auser access of a document on a user device, an amount of time spent bythe user viewing a specified content displayed on the user device, anumber of failed user login attempts, or a failed user transaction;determining, by the computer system based on the monitoring, that theuser requires assistance; predicting, by the computer system, apredicted user intent associated with the user based on the monitoring;determining, by the computer system, that a first communication channelcorresponds to the predicted user intent; causing, by the computersystem, a communication to be initiated with the user utilizing thefirst communication channel; detecting, by the computer system, a userinput through the first communication channel; analyzing, by thecomputer system, the detected user input; predicting, by the computersystem and based on the analyzing, a user-initiated intent, wherein thepredicting the user-initiated intent is performed separately from thepredicting the user intent; in response to determining theuser-initiated intent, determining, by the computer system, if thepredicted user-initiated intent corresponds to the predicted userintent; in response to determining that the user-initiated intent doesnot correspond to the predicted user intent, transmitting, by thecomputer system, a notification to the user device via the firstcommunication channel, the notification including a selectable element,the notification further including information corresponding to thepredicted user intent; detecting, by the computer system, a userselection of the selectable element; causing, by the computer system inresponse to the detecting of the user selection of the selectableelement, a second communication channel that corresponds to theuser-initiated intent to be utilized to communicate with the user, thesecond communication channel being different from the firstcommunication channel; and terminating the communication utilizing thefirst communication channel.
 16. The method of claim 15, wherein thedocument comprises a frequently asked questions (FAQ) document.
 17. Themethod of claim 15, wherein the determining that the first communicationchannel corresponds to the determined predicted user intent includes:accessing, by the computer system, a database; determining, from thedatabase, that a first plurality of communication channels areassociated with the predicted user intent; and selecting, by thecomputer system, the first communication channel from the firstplurality of communication channels as corresponding to the predicteduser intent based at least on a total weight score associated with thefirst communication channel.
 18. The method of claim 17, wherein thefirst plurality of communication channels includes the firstcommunication channel and the second communication channel, and whereinthe total weight score associated with the first communication channelis higher than a total weight score associated with the secondcommunication channel.
 19. The method of claim 17, wherein the firstplurality of communication channels includes the first communicationchannel and the second communication channel, and wherein the totalweight score associated with the first communication channel is lowerthan a total weight score associated with the second communicationchannel, and wherein a cost associated with the second communicationchannel is higher than a cost associated with the first communicationchannel.
 20. The method of claim 15, wherein the first communicationchannel or the second communication channel comprises an email, a textmessage, a phone call, an IVR call, or a chat session.